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Madness of the crowd: Understanding mass behaviors through a multidisciplinary lens - PubMed

  • ️Sat Jan 01 2022

Review

Madness of the crowd: Understanding mass behaviors through a multidisciplinary lens

Emily Brindal et al. Front Psychol. 2022.

Abstract

Mass or crowd behaviors refer to those that occur at a group level and suggest that crowds behave differently to individuals. Mass behaviors are typically triggered by a significant societal event. The ongoing COVID-19 pandemic has provided many tangible examples of crowd behaviors that have been observed globally, suggesting possible common underlying drivers. It is important to provide a deeper understanding of such behaviors to develop mitigation strategies for future population-level challenges. To gain deeper insight into a variety of crowd behaviors, we perform a conceptual analysis of crowd behaviors using three detailed case studies covering observable behavior (panic buying and health protective actions) and mass beliefs (conspiracy theories) that have resulted or shifted throughout the pandemic. The aim of this review was to explored key triggers, psychological drivers, and possible mitigation strategies through a mixture of theory and published literature. Finally, we create experimental mathematical models to support each case study and to illustrate the effects of manipulating key behavioral factors. Overall, our analyses identified several commonalties across the case studies and revealed the importance of Social Identity Theory and concepts of trust, social connection, and stress.

Keywords: conformity; conspiracy theories; crowd behavior; health protective behaviors; modeling; panic buying; social networks; social norms.

Copyright © 2022 Brindal, Kakoschke, Reeson and Evans.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1

Growth in household spending on goods, by category, Australia 2020. Source: Australian Bureau of Statistics, Insights into household consumption, December quarter 2020 3/03/2021.

Figure 2
Figure 2

Equilibrium levels of panic buying for products with differing visibility.

Figure 3
Figure 3

The small world model with N = 8, k = 4 and rewiring probabilities p = 0 (left), giving a ring lattice, and p = 0.2 (right).

Figure 4
Figure 4

Individuals’ initial scores. Any agent with a score above zero does the behaviour. In the ring lattice the ith agent’s immediate neighbours are the i−1th and i+1th agents. Since the agents are located on a ring, the neighbours of agent i=1 are agents i=2 and i=500.

Figure 5
Figure 5

Agents’ initial and final scores in small-world networks with different rewiring probabilities: 0.1 (A), 0.2 (B) and 0.3 (C).

Figure 6
Figure 6

The spread of a conspiracy theory in a population; around half of the individuals remain ‘infected’ with the conspiracy belief in this baseline scenario.

Figure 7
Figure 7

The spread of a conspiracy theory in a population, in which it is less likely that believers will be able to interact with other believers, resulting in a lower equilibrium number of ‘infected’ individuals.

Figure 8
Figure 8

The spread of a conspiracy theory infection through a population, where believers cannot reinforce each other’s beliefs. The conspiracy theory dies out under these settings.

Figure 9
Figure 9

The spread of a conspiracy theory infection through a population, with cumulative social influence from non-susceptible individuals on susceptible individuals. Again, the CT dies out as believers are convinced of their error.

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